With proliferation of electronic devices, such as laptops, smartphones, tablets, and/or the like, along with ever-increasing advancements and popularity of social media platforms such as FACEBOOK, LINKEDIN, TWITTER™, and/or the like, human generated messages have grown at a speedy rate. Further, the social media platforms may have alleviated the users to post and/or share the messages that may be representative of their respective characteristics such as likes, dislikes, needs, thoughts, and sentiments. Such messages may be of significance to a business organization. For example, the business organization may determine preferences of the users towards products and services, and accordingly, the business organization may recommend the products and services. In another example, the business organization may alter their respective business strategy to target such users.
However, such characteristics of the users may not be static in nature may change with time. The characteristics of the users may deviate or change based on future events, such as festivals, sports, politics, and/or the like. In such scenarios, predicting future activities of the users may be a non-trivial task.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.